{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "### 构建直方图提供两个data【y】bins[x]分布区间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-74.6896256692 81.0118721383\n"
     ]
    },
    {
     "data": {
      "image/png": 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SFoAkVcoCkKRKWQCSVCkLQJIq5VlAkvqq3QsSbllx5gDSaDL3ACSpUhaAJFXKApCkSnkM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\nklQpC0CSKmUBSFKlLABJqpQFIEmV+n/UVFHxY1dfZgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xabec400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.random.normal(0,20,10000)# 深刻理解随机数【x抽上符合高斯分布】\n",
    "print(min(data),max(data))\n",
    "bins = np.arange(-100,100,5) # 箱子的个数\n",
    "plt.hist(data,bins=bins)\n",
    "#修x抽\n",
    "plt.xlim(min(data)-5,max(data)+5)\n",
    "# 添加格子\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#直方图两个图查看重叠部分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JhTPoJalwBr0kFc6gl6TCGfSSVDiDXpIKV+YC0pJG3P1PvjjkseMLXcJ4rHBEL0mFc0Qv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\nBr0kFc6gl6TCGfSSVDiDXpIK9/8BH9Wf6NNpfoAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xaeeb320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data1 = [random.gauss(15,10) for i in range(500)] #需要在m=15，std=10[高斯函数另一种表达方式]\n",
    "data2 = [random.gauss(5,5)for i in range(500)]\n",
    "bins = np.arange(-50,50,2.5)\n",
    "plt.hist(data1,bins,label='class 1',alpha=0.3)#查看重叠数据\n",
    "plt.hist(data2,bins,label='class 2',alpha=0.3)\n",
    "#放上label位置\n",
    "plt.legend(loc='best')\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 散点图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 多元随机分布概念：\n",
    "http://www.cnblogs.com/qqhfeng/p/5294583.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mu_vec1 = np.array([0,0])\n",
    "cov_mat1 = np.array([[2,0],[0,2]])\n",
    "\n",
    "x1_samples = np.random.multivariate_normal(mu_vec1, cov_mat1, 100)\n",
    "x2_samples = np.random.multivariate_normal(mu_vec1+0.2, cov_mat1+0.2, 100)\n",
    "x3_samples = np.random.multivariate_normal(mu_vec1+0.4, cov_mat1+0.4, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0xc6663c8>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MjPTAZpvGwoW1WLx4CiMjPVmL40Qv99raCC5MO3A+0YYF8z+LxY2fR23tTVi0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\nqXTNqKRJUcqbLXTcKEGUIiVjmIPBHiQS07Baa9N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O+gxKLamjLqmjPrXXcq3t+VM5sMiy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\n/wAhDVztPmgLUAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc5eceb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))#定图缩放比例\n",
    "plt.scatter(x1_samples[:,0],x1_samples[:,1],color='b',marker='x',alpha=0.6,label='x1')\n",
    "plt.scatter(x2_samples[:,0],x2_samples[:,1],color='g',marker='o',alpha=0.6,label='x2')\n",
    "plt.scatter(x3_samples[:,0],x3_samples[:,1],color='y',marker='^',alpha=0.6,label='x3')\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 散点图如何标注注释坐标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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efWzbto309HTeeOMNrrjiCt/y0/3Dw8MZM2YMOTk5vnAuLy8nODi4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\n/wNf4s/9ZSK87AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8d16eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_coords = [0.13, 0.22, 0.39, 0.59, 0.68, 0.74, 0.93]\n",
    "y_coords = [0.75, 0.34, 0.44, 0.52, 0.80, 0.25, 0.55]\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(x_coords,y_coords,marker='s',s=50)\n",
    "for x,y in zip(x_coords,y_coords):\n",
    "     plt.annotate('(%s,%s)'%(x,y),xy=(x,y),xytext=(0,-15),ha=\"center\",textcoords = 'offset points') # textcoords：代表标注点模式"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 通过散点图的远近来看正太分布图的情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x9797860>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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NZsHzPAaDAWzbpgYjqqqi0+kAAEqlEj2RZbNZpNPpZxG9BYNBqggf3ex5ngfT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\n9Ho9dpgKBoP8XdRWaLfb6Ha7WFtbY3IiZcf9fh+qqj5pdFCSJIRCIb5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ulwuFQuFFVBrf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\n4gnx/wPJ1lsbO5GblAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9702390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mu_vec1 = np.array([0,0])\n",
    "cov_mat1 = np.array([[1,0],[0,1]])\n",
    "\n",
    "X = np.random.multivariate_normal(mu_vec1, cov_mat1, 500)\n",
    "fig = plt.figure(figsize=(8,6))\n",
    "# 离中心点越远点的面积越大\n",
    "R=X**2\n",
    "R_sum=R.sum(axis=1)\n",
    "plt.scatter(X[:,0],X[:,1],marker='o',s=20*R_sum,alpha=0.3,color='grey')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
